Trajectory tracking control for ships with fixed-time prescribed performance considering input saturation and dead...

Area of Science:

• Marine engineering
• Control systems theory
• Robotics

Background:

• Underactuated ships face challenges in trajectory tracking due to external disturbances, model uncertainties, and actuator limitations like saturation and dead zones.
• Existing control methods often struggle with fixed constraint boundaries and slow convergence rates.
• Addressing these limitations is crucial for reliable autonomous navigation and operation of underactuated vessels.

Purpose of the Study:

• To design a fixed-time prescribed performance trajectory tracking control method for underactuated ships.
• To overcome limitations of traditional methods by using adaptive prescribed performance functions and fixed-time convergence.
• To ensure robust trajectory tracking under unknown disturbances, uncertainties, and actuator nonlinearities.

Main Methods:

• Utilized barrier Lyapunov functions and prescribed performance functions to constrain position tracking errors.
• Employed Radial Basis Function (RBF) neural networks for estimating model uncertainties.
• Developed an adaptive control law incorporating fixed-time convergence theory and sliding mode surfaces.

Main Results:

• Proven global fixed-time convergence for velocity tracking errors through Lyapunov stability analysis.
• Demonstrated successful trajectory tracking in simulations despite actuator saturation and dead zones.
• Achieved significantly improved performance indicators, including reduced settling time and smoother input curves compared to traditional methods.

Conclusions:

• The proposed fixed-time control method effectively enables underactuated ships to achieve precise trajectory tracking.
• The approach offers enhanced robustness against disturbances and actuator nonlinearities.
• The controller's performance is superior to existing methods, aligning better with practical engineering requirements.